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This method performs comparably to strong branching on MIPLIB, and better than strong branching on hard real-world procurement optimization instances on which CPLEX’s default strong branching outperforms CPLEX’s default branching strategy. The second family combines this idea with strong branching. The third family does not use lookahead, but instead exploits the tie between indicator variables and the other variables they govern. This significantly outperforms the state-of-the-art branching strategies. The fourth family is about branching using carefully constructed linear inequality constraints over sets of variables.","doi":null,"url":"https://ijcai.org/proceedings/2007/368","pdf":"https://ijcai.org/proceedings/2007/0368.pdf","markdown":"https://ijcai.org/proceedings/2007/368.md","bibtex":"https://ijcai.org/proceedings/2007/bibtex/368","volume":{"slug":"2007","title":"Proceedings of the Twentieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2007","url":"https://ijcai.org/proceedings/2007/","year":2007,"location":"Hyderabad, India","dates":"","editors":"Ramon López de Mántaras","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":368,"pages":{"first":2286,"last":2291},"keywords":[],"videos":[],"references":[{"position":1,"raw":"[Achterberg, 2006] Tobias Achterberg. Conflict analysis in mixed integer programming. Discrete Optimization, 2006. 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